A tropical butterfly’s wing pattern shifts with the seasons—and that visible flexibility holds the key to predicting which species will survive climate change. The problem is that current models for assessing climate risk ignore how organisms actually adapt. They treat species as fixed, when in reality many can adjust their bodies and life cycles in response to environmental cues—a phenomenon called plasticity. But climate change is making those cues unreliable, and some populations have already lost the ability to evolve new responses. The researcher has shown this capacity is absent in some groups. The gap is that no one has connected the molecular machinery behind plasticity—the genes, hormones, and developmental pathways—to the real-world data that conservation biologists use. If this works, it will produce a practical tool: a way to predict evolutionary resilience from a field-collected DNA sample and local climate data. That would let conservation managers identify which species are genuinely at risk and which can adapt, without waiting for populations to crash. The research is fundamental science—it asks how development and evolution interact—but it builds directly toward an actionable vulnerability assessment system.
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The world's climate is changing at an unprecedented rate, with dire consequences for biodiversity and ecosystems on which we depend for our survival. To have a chance at managing this transition, we urgently need to identify which species are at risk, and what determines their fate. One key route to resilience is to evolve rapidly enough to keep up with climate change. Unfortunately, the factors that govern limits to and potential for rapid adaptation are poorly understood, and consequently we lack actionable tools that allow us to predict which species can adapt, and where they are vulnerable. Plasticity is the ability of individuals to exploit predictive environmental cues in order to optimally match morphology, behaviour, and life cycle events to current or future conditions, for instance between seasons. It is accomplished via developmental cascades that translate cues into coherent trait changes, via sensing mechanisms, hormonal signalling pathways, genetic regulators, and ultimately downstream effector genes. The growing concern is that climate change is making cues less reliable, as well as changing the optimal balance between traits. Under climate change, previously adaptive existing plastic responses are now leading to mismatches between the environment and expressed traits, and unless populations can rapidly evolve new responses, they may face extinction. I have already demonstrated that capacity to evolve is absent in some populations. Progress to understand limits to rapid adaptation, and in particular the role of plasticity, has been hampered by fragmentation across disciplines. While mechanistic biology has made great strides in disentangling the gene networks and developmental pathways by which the genome makes a multicellular organism, the role of the environment has typically been ignored as noise. Worse, most studies have been carried out in artificial lab environments, far from the complexities of the real world where plastic responses evolve and where they could potentially aid climate resilience. On the other hand, predictive models of climate change resilience which guide species vulnerability assessments suffer from limited explanatory power as they ignore important biological mechanisms such as phenotypic plasticity, adaptation, and genetics. Rapid adaptation is particularly poorly integrated into these resilience models, due to lack of high-quality empirical data and analytical methods to integrate different types of data. I have pioneered integrative approaches that bring together developmental, evolutionary, and ecological analytical methods, and have set up tropical butterflies as a powerful model to implement this agenda. Excitingly, new analytical methods in DNA sequencing, genetics, and statistics now hold the promise to connect previously disparate fields. My multidisciplinary research places me in a unique position to exploit these new technological developments, and realise adaptive capacity as a common currency between mechanistic and conservation biology. Specifically, is genetic variation at key regulatory hubs of developmental pathways that regulate trait expression. Importantly, developing this common currency will enable new tools to predict evolutionary responses to climate change from field-collected DNA samples and climate data. A FLF would provide me with the opportunity to deliver on this transformative research agenda, and establish me as a leader in the field of Eco-Devo and climate change biology.
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